Episode Transcript
[00:00:00] Speaker A: Thanks for being here today. I'm Scott Schiff with the Atlas Society, and we're very pleased to have Atlas Society senior fellow Rob Traczynski talking about getting lost in model land. After Rob's opening remarks, we'll take questions from you. So if you want to request to speak, you know, we'll try to get to as many of you as possible. Rob, intriguing topic. Let's hear about model land.
[00:00:24] Speaker B: Okay, so, thanks, Scott. This is part of the work I'm doing on an upcoming book, looking at Ayn Rand's, Ayn Rand's whole philosophy, but especially also looking at her, including in that is looking at her epistemology, her theory of knowledge, her theory of how do we look out at the world and observe and gain an understanding of the world. By the way, I just wanted to check, before we get started, I'm sort of. I've been talking. I've been doing these in a new room of the house we just renovated, and a lot. Last time it was really bouncy because there was no furniture in here. So how is it doing today? Is it better?
[00:01:01] Speaker A: Yeah, there's a slight echo, but I think it sounds good.
[00:01:04] Speaker B: When we get the carpet in here, it'll be better. There's a rug coming in here to get better. I just want to make sure it wasn't too bouncy for the talk here. All right. So anyway, that's just housekeeping stuff. All right. So talking about Ayn Rand's theory of knowledge, and one of the things I want to contrast it to is one that I think is very common, very widely accepted, and is, has certain negative consequences in terms of a way that people look at how you gain knowledge of the world. And it's one that sort of throws people off.
And the best way to summarize this up is that it is a theory of that in understanding the world. What we do is we make mental models of the world. So the idea is that abstract knowledge, knowledge of, you know, theoretical knowledge about the world, scientific knowledge about the world, philosophical knowledge about the world, that these are all, quote unquote, mental models of the world. And so what we're doing, we're trying to figure out whether our model is valid or true, is we're trying to compare the model to the data from, from the real world.
Now, I.
This is part of a wider idea called representationalism that I'm going to get around to. But it's the idea that the most sort of common and in some ways the most extreme version of this, I came across is from the 20th century philosopher of science, Karl Popper. Now, he's probably the most well known. I think he's the most. In my experience, he's the most popular philosopher of science among actual scientists because, you know, and I think for valid reasons, which is that, you know, there's a sense that a lot of the 20th century philosophers of science were out to sort of take science down a peg. They were out there to say, oh, science doesn't have this special claim to knowledge. It's no more valuable than anything else. There's no more valid than storytelling. And there's, you know, I think Thomas Kuhn is one of the people I like to use as my example on this. Right. There's this idea that, well, you know, scientifically, knowledge is just this consensus, this paradigm that you form by social consensus, and it's really no more valid than any other form of knowledge. And so there's this. There's a sense among philosophers of science. There's been a certain trend of what I think it almost seems to be motivated by a kind of jealousy. It's like here we are, we humanities people. We've been out here arguing back and forth with each other and spinning theories and never really getting anywhere and never actually getting to the truth. And then here the scientists come along and in a couple hundred years, they put a man on the moon. And, you know, they've outdone us so badly that, you know, we feel like we have to, you know, there's a sort of resentment of they've outdone us so badly, we have to take them down a peg somehow, show that although this is really just an illusion, they haven't actually done anything better or different than the humanities people. So that, you know, Thomas Kuhn, who I guess that I like to beat up on, has this whole weird section in the structure of scientific revolutions, his main book, where he tries to take on this idea of, well, why, you know, science put a man on the moon. Isn't that show they've done something? He said, well, you know, they've created some knowledge, some techniques that are better for one particular goal but maybe not better for other goals. And he tries to subjectivize the whole thing and sort of make it, you know, try to wriggle out of this idea that while putting a bat on the moon is kind of proof that you have gained valid knowledge. All right, so in contrast to that, Karl Popper, I think, is liked by actual scientists because he seems like he's trying to create, you know, an objective standard by which scientific knowledge can be created that you could test it against data.
Now, he says, you can't prove something absolutely true. You can falsify it, but, you know, there's a sense of easy trying to capture and trying to preserve or celebrate the science, you know, what's happening in science rather than tearing it down. So that's why I think Popper is so influential. But this idea of the mental model, this is very central to Popper's idea. And I think this is where people pick up this particular sort of distortion of how to think about the world. All right, so let me talk about what Karl Popper's most extreme version of this.
So in 1967, I came across this in 1967, he gave a lecture presenting a theory of the three worlds. I call this third world epistemology with some implications there. He had this theory of the three worlds, and, and just briefly summarize this, and this is that there are three worlds we all live in. So world one is just the world, the real world of actual things, or the real world out there, if you want to call it that. World two is a world of mental entities that consists of the sort of the perceptual or experiential level of consciousness. So every time I have, you know, I have context of the world, I have perceptions, I have images and things like that that pop into my mind, images that correspond in some way to the things out in the world.
And so that's its own sort of mental world of images and perceptions that forms inside my brain.
And then he says there's a third world.
On the basis of observing this world, too, you have this sort of internal process of observing the world, too, the world of mental entities, of perceptions inside your brain. So there's like a little faculty inside of you that observes those mental entities inside your head, the world, too. And on that basis, you construct world three, which is a conceptual level, theoretical model or reconstruction of world two.
And so this is kind of a mind bending idea, and I haven't seen it used very often explicitly, but I think it's implicit in a lot of what Karl Popper is doing, a lot of what he put out into the world. So if we could visualize, give you visuals to sort of work on this, to understand this the way I would describe world one, you know, world one is a billiard ball.
I came up with these examples, by the way, in talking about causality, where you have billiard balls as examples of causality have been used since at least the time of David Hume. So an actual. The actual billiard ball in reality is the world one. World two would be an image of a billiard ball in your head. And then. So you'll sort of.
I use this. I use a photo where. So it's like a two dimensional projection or image in your memory of what a billiard ball looks like. So that's. What's world two? World two is composed of those things, all these images in your consciousness. And then world three would be your picture. A schematic diagram of a sphere, right? So it would be the image of the billiard ball, but shorn of all the details, stripped of all specific aspects of color. And what, maybe there's an eight. It's an eight ball. So there's a. It's black with the white center and the eight written on it. All that stuff is taken out, and you've reduced it to sort of a framework diagram or schematic, right? And that's, you know, you have the equator and you have the radius of the sphere, and you've reduced it to the mental entity of a theoretical sphere. So that's sort of an idea of what he's getting at with this world one, world two, world three. And this is the idea that the conceptual knowledge, abstract knowledge of the world, is some sort of schematic model built in your head that is supposed to correspond in some way or be able to predict what's going on in world two, which is then connected in some mysterious way to the real world. Right? And it's always, not always clear how it's connected to the real world.
All right? So. And this is very much how popper thinks science is done. It's just that while you go around, you create these mental schematics, these mental models, and it's more like these mental models are sort of like a laboratory where you create these mental models. You use the mental models to deductively create predictions about what's going to happen in world two, the world of your perception. And then you judge your models by whether or not how well they produce the predictions for the data that appears in world two.
So you'll notice one thing about this is this is very, you know, abstract theoretical knowledge is very, very, in this industry, very disconnected from the real world. I like to use the phrase the real world out there because that's, you know, how people think about it, right? It's like you are stuck here in your brain, and the real world is maybe somewhere out there. And if you find yourself, by the way, my advice, you find yourself using the word, the phrase the real world out there, you really have to rethink your assumptions, because the real world is not out there. You are in the real world, right? You are in and surrounded by it and impinged upon it and connected to it in a million different ways. But if you find yourself thinking about the phrase the real world out there, you've already accepted this sort of inverted idea of what, of what consciousness and how the brain works and how we get knowledge of the world. And that's. But that's very much what popper has done. He's the real world is world one. It's a toll. It's not. It's not even the world you're in. It's totally different world. The world you're in is this world of images. And then on the basis of images inside your mind, and then the images inside your mind produce another world that's like even more inward, even more isolated inside your head, which is this world of abstract schematics that somehow are going, that you hope will correspond or accurately predict the results of the world of mental images.
And again, you're getting a greater remove from the world each time.
Now, a lot of this is reflecting a longstanding idea in consciousness. I think it's the one thing people get most wrong about understanding how knowledge works and how perception works. And it's called representationalism. And this is the idea that when you, when you observe the world or when you encounter the world impinges upon you, however you want to put it, that what happens is that a set of images is created inside your brain that are sort of representations of the world, and that you're not perceiving the world directly. You're perceiving these representations of the world that are recreated as images in your brain. Right. The way I would think about it is think about schematic. The schematic I use, this is not a visual medium here, so I have to describe it. The schematic I use is of, you know, there's the world out there, and then there's your head, and then inside your head there's like a little tv screen. And on that little tv screen is.
Is a bunch of images that represent what's that, that are supposedly represent what's going on out in the world outside of you and your consciousness is this other little head, this other little guy inside your brain, looking at that, at that tv screen. Now, I just realized that I'm trying to struggle to describe these mental images. I don't need to work so hard at it anymore, because some of this has actually been put into fiction or into the films. So think of the matrix, right? So this is sort of the matrix view of the world. The idea that, you know, we're brains in the vat, and we're being shown these sort of simulated images, and you're literally looking at a television screen that represents, inside your head, that represents what the world is.
[00:13:11] Speaker A: All right?
[00:13:11] Speaker B: So think of it that way. So then the thing about this idea of consciousness is creating mental models of the world, and that's how we understand the world. That's what abstract or theoretical knowledge consists of. It is that, uh, you have to think about. So I had that, you know, there's the real world out there. You have the inside your head, there's a little screen showing images, and then you have another little guy, another consciousness inside there. Looking at those images inside your head, you'd have to nest that another level. So the theoretical level, the conceptual level, the, the level of abstract thinking, would be another little screen inside that small, smaller head and another little guy looking at that, right? This very strangely nested thing. And of course, you know, if you think about it, if you take that really seriously, you'd have to. Well, how is that little consciousness inside the consciousness? Inside the consciousness? How is that perceiving anything? Well, there has to be another little consciousness inside him, and it would be this infinite regress, and you begin farther away from reality each time. So that gives us an idea of what the problem with this approach is, this idea that all we have are mental models that we can sort of vaguely compare, and we can project the data and see if the predictions line up with our perceptions, that this is getting us off the track of how consciousness actually works. Now, I want to talk about how con, what I think the answer to that is how conscious actually does work in relation to that. But one of the things, so there's a book I've been checking out, and I haven't gotten very far in it, but I like the approach of what it's called lost escape from model land. And it's published recently, and it's making the case that people get too caught up. Scientists especially get too caught up in their models, and they don't realize that the model is not the real world. The model is just a way of simulating or trying to capture, kind of understand something about the real world, but it is not, the model is not the end, uh, goal. The world is the end goal. You know, the world is the real world is the standard. And you can see people getting lost in these models in a number of different ways.
Um, you know, there's an old saying, the map is not the territory, right? And this is, I think, captures the idea that you have the map. Uh, if you have a map as a schematic, it's a world three kind of thing. It's a mental diagram representing the world out there. But there's a difference between, the map is simplified, it is generalized. It leaves a lot of stuff out. It's not the same thing as actually being in the territory, walking around, seeing the concrete things you see out there. So one example I want to point out to this is because I think it's one that where this intrudes into our political debates and our larger cultural and social debates is this idea of global warming. So how is it we know that global warming is going to happen, that it's going to become catastrophic, that it's supposedly going to have all these horrible results? Well, primarily the big evidence brought up for it is models. People have created climate models, computer models of the climate that are supposed to project what's going to happen with the climate 100 years into the future. And the fact that you can create these models, you can churn out these models, they produce certain results, is taken as evidence of, oh, we know this is going to be catastrophic, but this is almost entirely done, deceased, especially in our political debate. The scientists, some of the real scientists who do this are much better about this. But when this filters into the political debate, where people have this obvious interest in hyping the thing, obvious political interest, you know, it serves some goal that they want politically, there is this tendency to drop the difference in reality in the model and to, to not, you know, to refuse to acknowledge the limitations of a model. The fact that it is simplified. And I think in some of these cases oversimplified the fact that, you know, what the, the climate of the entire planet over a period of 100 years is phenomenally complex. And so to make a computer model of it, even a very complex computer model, you are radically simplifying it and making all sorts of assumptions. And those assumptions can influence, you know, you have assumptions about what's the responsiveness of the atmosphere in terms of how much extra greenhouse gases will produce, how much warming. Well, we don't actually know the answer to that. So you have to make assumptions about what that responsiveness is. And those assumptions, when you put them into a computer model and you turn it around, they can get amplified and produce all these results. So you actually have this tremendous amount of difference between the different models. And then you have the observed results which to this point generally fall below that of the at or below that of the lowest results from the models. So you have a clear issue here where there's a difference between reality and the models, that the map is not the territory, but you have this outlook of no, we created these models, therefore this is really solid knowledge. This is science. We should all act on it immediately, instead of waiting to see how the models turn out, how accurate they turn out to be. Now, by the way, I want to say a model per se is a useful tool epistemologically, but it's a useful tool so long as you remember that it is a model, that it is simplified, that it is, and there are reasons to simplify something, to create a model of it. And some of the reasons are that you have, let's say you have imperfect knowledge of all the exact details.
So you have to create a simplified model because you don't have, you can't create something more complex, but you're creating a simplified model to see what that model will tell you, so you can ask better questions and make better observations. You know what to look for to see if you're on the right track or the wrong track. But then you'd have to be very careful to make sure that you remember your simplified model is missing data or missing something. Or there could be cases where, you know, the reality is more complex, you can measure it, and you actually know how to account for the greater complexity of the real world compared to the model, but for to make the computation simpler, you realize that, well, if I leave out some of the complications, I will still get a result that's good enough for the purposes I'm using for, you know, it'll be within the tolerance of accuracy that I need, and it'll make the computation simpler. So I'll do a model. And so there are all sorts of reasons why you would want to do use models in a valid way, but they all have to take into account the fact that the model is not the same thing as the reality and that you know what you're putting in and what you're leaving out of the model. You know what your assumptions are. And so you know that this is an abstraction that is simplified and taking away and has somehow taken away from the details.
Now, to get to what I think is the right view of conceptual knowledge. Now, this is whether you can use models validly within this right view. So it's not so much that models, per se are invalid. But to contrast it to what full knowledge of something is, as opposed to the model, which is sort of a simplified or artificial version of the more complex knowledge that you get from observing reality directly. So just to indicate what that would mean. So this is one of the key things in Ayn Rand's, in the objectivist epistemology, and Ayn Rand's view of the nature of conceptual knowledge is that her idea was. So this all goes back to, actually, this view of models. I talked about, Karl Popper. But where it ultimately goes back to is there was a theory of concepts that was very common in the enlightenment era.
That was, like, the best way to describe it is that is, it has a sort of schematic approach to conceptual knowledge, that in creating a concept, you know, if I have a concept of man, it's. I call it the stick figure theory of concepts. So if I have a concept of what a human being is, a concept of man, what I would do is I would abstract away, create this sort of schematic of, you know, it's because some men are taller and some are shorter, some are fatter and some are thinner. Some are, they have different color skin. They have all these different characteristics. So you simply drop out and, and ignore all those other characteristics. Those characteristics are irrelevant. And then you, you, you, in this view, you. You reduce the concept down to a sort of schematic. You know, so I talked about the. The billiard ball, and then you have the image of the billiard ball. Then you have this sort of schematic of a geometric schematic of a sphere, right? You do the same thing for human beings. You come to this sort of schematic, stick figure version of what a human being is, which is stripped of all specific characteristics. And just this sort of abstract schematic. And that's what the concept is. And Ayn Rand was arguing against that viewpoint. Her viewpoint is that when you form a generalization, so a concept like man or furniture or chair, what you're doing is you're taking all the observations you have, all the things you observed, the specific examples you've seen of it, and you're not getting rid of the specific details. What you're doing is you are finding some real similarity. You have to find some real, genuine, objective, directly observable similarity among these things. You're focusing on that similarity and using it to group all those things together into the members of a class or a group. You know, all these different creatures are men. They're human beings, as opposed to dogs, cats, other animals, inanimate objects, etcetera. So what you're doing is taking this group of things that exist out in the real world. You're observing them in the real world, and then you're taking those real world observations and you are taking a certain perspective on them. You're saying, well, I can view these things, mentally view these things as all members of a class of similar things because of some, you know, because of certain, certain directly observable similarities they have. But in doing that, at least to form a proper concept, a concept that's really grounded in the facts of reality, you're not dropping out and sort of carving away all the specific details. You are focusing on certain things that are similarities among them, but you're keeping all the details because ultimately the concept is really is just that group of things out in the real world looked at from a certain perspective, from a certain mental perspective, right? So it's, uh, uh, you know, it's, it's similar to how, um, you know, if, if you are, if you say, if you are looking out, you say, let's look for all red things. You know, you say, you look at a giant crowd of people, you say, I want to look at every, look at everybody who's wearing a red coat, right? You can mentally sort of look out and give your brain the command, I want to observe everybody who's wearing a red coat. And then you'll see this, like dots of red all throughout. And that's in, and in your mind, what you're doing is you're still looking at the crowd. They're the same people, the same crowd. You're not ignoring anything, you're not missing anything, you're not carving out real facts about this. But by looking at the crowd in that way of saying, I'm going to focus specifically on Red coast, you'll see, dot, dot, dot, dot, dot, there they all are. You are seeing those things as a group from a certain perspective. And that's sort of a certain mental perspective. And that's what she's getting at in her theory of concepts. And what it does is it creates, it takes this world, one world, two world, three approach that we were talking about, and it collapses it all back down to you still just have one world, right, the world of things out there, and your consciousness is in contact with and observing that world. And then when you make abstractions, you are then observing that world from a certain specific mental perspective that allows you to see the thing. You're still observing the same world. You're seeing it in a slightly different way. You're getting different things out of it because you're observing it from a perspective, but you're not observing something different. You're not creating a new world or a new class of mental entities that you're then observing. You're creating the same old world one, right? So there's just one world. We don't have to create a second one and a third one in order to account for perceptual knowledge or for abstract and conceptual knowledge. And so if we keep that in mind, then you could create a model. But a model is just a tool for helping you better understand what questions to ask about the real world that you're actually observing.
So that's a long, complex and description, but I wanted to sort of take that on because of, I think this idea of abstract knowledge and theatrical knowledge of the world consisting of model making about the world, tends to turn people inward to this sort of mental world and to creating ever more abstract and complex models and sort of living in the world of models inside their head and not focusing on the question of how do you connect your abstract knowledge to the actual, you know, perceptually observable, you know, directly encountered facts of the real world. All right, so I think I time to stop for questions, comments, other examples people can have of how they've encountered this sort of model making approach to thinking.
[00:27:19] Speaker A: Great. And yeah, if you want to participate, just click request to speak.
You know, in the meantime, even with global warming, I mean, you were assuming, you know, I think some being mistaken. But what about, you know, where there are these kind of agenda driven data scientists that start with a hypothesis and try to tweak the data to match it?
[00:27:43] Speaker B: Well, do you have a specific in mind or just a general?
[00:27:46] Speaker A: I mean, even with like, globe, you know, climate change, they can, you know, they talked about that in climate gate. They're like, massage the data until it reads what you want.
[00:27:56] Speaker B: If you torture the data, it will confess.
That's actually a saying, you know, this sort of sardonic saying among scientists, because, you know, they're, they know that the danger there is that you could. Yeah, and then that's the thing is that, um, I even encountered there was, I won't say who, but there's, there's a, there's an objectivist philosopher or historian who was his historian who was doing this once, this is years ago, and I'm not going to go into details, but he said he had this approach of, well, I have this theory. And so I went and started looking for facts from history that fit the theory. And I thought, well, there's your problem.
You started with the theory. You went looking for facts to fit it, right? And that's sort of the, it was the problem, I thought, with the way he approached the thing.
And you. It's a real ten. I think it's the. I like to say it's the occupational hazard of intellectual types, right? That we. So that we tend to. The problem with intellectuals is they're interested in ideas as opposed to being interested in the facts to which the ideas were supposed to refer. And so we can get so enamored of the theories and models we have in our head that we start with that and we get, we build palaces of theory inside our head, and then we go looking for facts to support it. And obviously, if you go looking for facts to support a theory, you're probably going to find some, right? If that's all you're looking for, if you're giving your brain, let's look for facts that support my theory, you're probably going to find some, as opposed to saying, let's look at all the facts. And then, you know, see what theory emerges from that. You know, instead of looking at all the facts and seeing, you know, is this perspective I have on the facts?
Is it one that's viable? Is it one that works? Or is it one that, you know, I can fit a few facts into it, but the, the whole, the whole pattern of reality doesn't, doesn't match it.
And I was, I would also say, I think this is. I meant one of the reasons I mentioned this is there is, and I'm. One reason I mentioned it specifically on Twitter spaces is I think that there is kind of a Silicon Valley tech bro kind of attitude that comes out of this, which is because, you know, if you're a tech guy and you're used to writing code and computer software, you kind of want all, you know, it's writing code and computer models and creating computer software is what you're good at. You kind of want all the world to be code, right?
You kind of want everything to be solvable by. If I just write the code, write code and input it, I can make the world do what I want it to do. I think this, there was a fad for a while. I think it's still around there of this sort of pickup artist kind of lingo about relationships and, you know, this very mechanistic model of how romantic relationships work and how to, how to get a woman and how to have a relationship with a woman. And it's, and it's very much in this sort of mechanistic mode of, well, you input certain data and that you game the system in a certain way and you get a certain result coming back out. And I think this, this sort of tends to spread in the tech bro kind of culture that you often see on Twitter, because, again, it's, you know, if you're really good at manipulating code, you're really hoping the whole world will just be a matter of manipulating code. And you also see it. I think there's a, Scott Alexander is a guy who does he used to a Slate star Codex. I think it's astral. Codex ten is the new version of it. It's a subsect blog. He has, he has some really interesting observations to make sometimes, but I get really kind of frustrated with him other times because he has to be very satisfied with this very let's create, let's construct a mental model of the world and then make deductions from that mental model as a way of thinking about the world. And oftentimes when I'm sitting there saying, you're thinking, you can just go observe the world directly and see how things work. And it's actually much easier to understand things if you do it that way, as opposed to, you know, to, to constructing this very complex mental model and trying to deduce from that. So it's, it is a common and widespread attitude or approach.
[00:32:09] Speaker A: Great. We want to encourage people to join us with questions. We have our founder, David Kelly. Welcome.
[00:32:18] Speaker B: Hey, Scott.
[00:32:19] Speaker C: Hey, Rob.
Fascinating talk.
To me, as an epistemologist especially, I have a question.
You know, a lot of what you said, I totally agree with, about model building. And it's, you know, the realm in which I've seen it at its worst is economics, where people, you know, devise all these economic models and then expect, you know, this complex, incredibly complex economy to conform or predict. I'm not an economist, so I can't judge them particularly, but I just think it's an exercise in a lot of a priori thought. But I do have a question that when we are acquiring knowledge, we start with what we can observe, and we form concepts for observable things. But, you know, we progressed a long way, and the concepts become more and more complex and more dependent on previous concepts, and so do our theories and observations. And so in addition to the standards of evidence for a given conclusion, there's also the standard of integration and consistency with the rest of what we know, which could be thought of when you get into complex areas of science as a kind of systematic view. Anyway, I don't know if I agree that it's called a model, but I think that's what at least some philosophers of science are getting at with that when they use that term. Anyway. Does that, does that fit with your conception? That's the question, yeah.
[00:34:06] Speaker B: Yeah. Well, yeah, that's an interesting thing. I think the systematic thing doesn't necessarily mean a model, though, because what it means is that when you're, you're, you're integrating something into a whole system of other knowledge you have. You're integrating it with other knowledge. You have other things that are, that are based, that you've other observations you've made and the results of those observations, you know, so I'm trying to. There's a way of describing that.
Yeah. I think where, where it becomes a problem is actually, is when you have a very narrow specialty. Right. And then you're integrating it with things from other specialties where you don't have access to all the observations. Right. So you don't have, you're sort of taking, you're assuming that the knowledge produced in that other field, often validly assuming that the people working there have figured something out. That's correct. But you don't have full firsthand knowledge of what it is. So as you get to the fringes of your own sort of specialized knowledge, you sometimes are acting on a simplified model, create, you know, taken from somebody else's work, where you don't have access to all the data or all the observations, all the complex knowledge, you know, because the world is limited. You are limited. You're one person. Your lifetime is limited. You can't, you know, you can't become an expert in quantum physics and biology necessarily at the same time. So, you know, you sometimes are taking things in a simplified model form where you don't have all the direct knowledge, and yet the two fields do need to be integrated. You have to somehow connect what you're doing with what's going on in that other field. And I think that leads to, you know, possibly to unavoidable, to unavoidable problems where you are connecting it to something you don't fully understand. And, you know, there might be, and I've seen specialties arise in the connections between fields.
[00:36:00] Speaker C: Right.
[00:36:00] Speaker B: Because there is a need for somebody who actually understand both sides and try to figure out how they go together without messing up either one.
[00:36:08] Speaker C: Yeah.
[00:36:09] Speaker B: And I think that what you're speaking to more widely and the reason why model making. And the model view, I think, really arises is because at a certain level, yes, we do get to more abstract knowledge where we've gone from what can be observed directly. So if I'm, if I'm, you know, classifying furniture, you know, chairs, tables, armoire, or whatever really complex bookcase, I'm looking around the room here trying to classify these desk. If I'm classifying furniture, it's all based on stuff I can just observe and look at directly. If I'm classifying subatomic particles, right? I'm not talking about something I can observe directly. Now, there are things I can observe directly, right? There are experiments you can do when you get the, you know, and you get visible results.
And then, you know, from, based on those visible results, you are inferring something that's happening on a micro scale that you can't observe directly. And so when you get to that point where you are describing things that are either too big, you know, the structure of the galaxy, or too small for you to observe directly, it's easy to fall back on. You know what? You kind of need a mental model. You need to use models that are simplified versions. So a great example of this is the old one of, well, what's the. How does what. How does. What is an atom like? Well, you have a nucleus, and there's a protons and neutrons in the middle, and there's these little, then you visualize these little, like billiard balls sticking together in the middle. And then, you know, circling around them, orbiting around them, sort of like planets are the electrons. And this is the common. If you, if you went, it's probably learned this in school, the common model for what the atom looks like. And then, of course, people come along and they say, oh, well, now we've got new knowledge from quantum physics and, you know, the Higgs boson and whatever else. And, and we know that's not really true. That's not overly simplified model. And people use that to say, see, therefore, we've overthrown previous knowledge. Well, no, you've overthrown the previous oversimplified model. You haven't overthrown the actual body of observations and connections and theories that, that referred to. So, you know, again, if you, if you take the model too seriously, it makes the model your goal, rather than the facts and observations that it refers to. And that it's that the model is sort of trying to gather together and help you understand, then you can get to this idea that, well, if I have a, if I have a simplified visual model, I created of something that's not visual. And then that model turns out to be wrong. You didn't. You could think, oh, I overthrew this. Overturns all existing knowledge. The old paradigm, as Thomas goon would say, has been demolished. Well, what you've actually, what you've. What you've overthrown is the simplified tool that you created to help you visualize this, but not the actual knowledge, the actual observations.
[00:39:12] Speaker C: That's.
[00:39:13] Speaker B: I guess that's my thing. Soapbox on that.
Okay.
[00:39:16] Speaker C: Yeah, thanks. That sounds great, Rob. Appreciate it.
[00:39:21] Speaker A: Great. So it. I mean, are concepts, to a degree of representation of reality?
[00:39:28] Speaker B: Well, see, that's the re presentation that I'm arguing with. So concepts are a. And this is what the real. I think the radical heart of Ayn Rand's work on epistemology and her, especially her theory of concepts review of what abstractions are, is that abstractions are not a representation of reality. So representation means reality is out there, and then I'm creating something new that represents it, right? So if I were creating a representation of the death of Julius Caesar, right? I go up and perform a Shakespeare play, and it's a bunch of guys. It's not Julius Caesar being stabbed by Brutus. It's a bunch of guys on a stage pretending to be Julius Caesar and imagining what he might have looked like and what people might have said. And, you know, speaking the immortal lines of Shakespeare. It sounds like a good way to do that, but that's not Julius Caesar.
[00:40:18] Speaker A: Right.
[00:40:18] Speaker B: So that's a re presentation, and that's what we're not doing with the concept of the valid concept. If you really understand something, you are not taking reality and representing it in some artificial form.
Her radical heart of. The radical heart of ein rance. Epistemology is that an abstraction? A concept is a perspective on the real world. So you are directly observing the real things, but then you are taking a certain mental perspective. Like, you know, like, I think that analogy, I came up with it just now, but I like it better than what I've come up with before, which is this idea of looking at. You imagine a massive crowd of people, tens of thousands of people, all wearing different colored clothes and coats and hats and what have you. And you say, I'm going to look at the. I'm going to. I'm going to look at this and ask, who's wearing a red coat? And then you can see how you get this mental perspective. You're looking at the same crowd. Nothing's changed, nothing's represented, nothing. You're near, you're not taking all the people red coats and pulling them out into a separate area. You're looking at the exact same crowd. But if you say, just look for the red coats, you can focus and see them as a pattern, as a thing jumping out from mentally isolated out. Now, they're mentally isolated, but they're not actually isolated.
[00:41:33] Speaker C: Right.
[00:41:33] Speaker B: So you have this perspective on the crowd where you look at it from the perspective of who's wearing a red coat, but nothing about the crowd itself has actually changed. So that's why it's not a representation. It's a perspective. Now, looking for people of red coats is probably not an exceptionally useful category. Right.
[00:41:51] Speaker A: Well, you can think about things that aren't there. And I guess, you know, the other thing, it's just that when you omit the measurements, as Rand said, it becomes different than that thing in front of you, necessarily.
[00:42:04] Speaker B: Well, so that's the thing is, I think some people take, and that's like a misinterpretation of what her theory of concepts is. So she said, what you do is you omit, these people have all different measurements.
Like I said, some people are taller, some people are shorter. So you form the concept of men. You omit the measurements. What she means by omit the measurements is not that they are actually removed.
[00:42:25] Speaker A: Right.
[00:42:25] Speaker B: It's not that they are consigned and stripped out mentally. And that's that. I think the key misinterpretation is I don't think that's what she's saying. And I think when people interpret it that way, they get to this sort of older idea that the stick figure view of a concept.
[00:42:40] Speaker C: Right.
[00:42:40] Speaker B: So you're stripping out all the individual measurements and you're just ending up with this six figure schematic. What she means by omitting it is you are mentally. Is that you're. Is that you're. It's out of you. You're not, you're not.
It's not central to your perspective. Right. You're putting it. You are, you are focusing. You are selectively focusing on other. On something else other than the specific measurements. So it might be the shared characteristic. You're focusing on the fact that they share a certain characteristic and not focusing, sort of putting less de emphasizing. So de emphasizing might be a better word, de emphasizing the differences in that particular characteristic. So everybody has some height, right? We're not disembodied, non spatial beings. Everybody has some height. But what exact height you are? Well, it doesn't matter. We're going to de emphasize that mentally. But you're mentally deemphasizing it doesn't mean stripping it out and getting rid of it and turning and reducing everything down to a schematic. And that's, I think, the real heart of what I'm getting at with this idea of not viewing things as a schematic or a model of reality. That conceptual knowledge, ideally is real. Conceptual knowledge is reality observed by you directly, with you using a certain mental perspective to emphasize one characteristic for a certain purpose you have at this point, and de emphasize other characteristics that don't matter for your current purposes. And then at another time, you'll. You'll emphasize a different characteristic. But you. It's all. It's what's. What you're observing is reality from a certain perspective.
Your changes in mental emphasis change your perspective on those real facts.
[00:44:24] Speaker A: How about speaking of these models?
Musk and other people say that it's at least possible we're living in a simulation, even if the belief is likely wrong. Some of these models don't necessarily stop a person from being creative.
[00:44:44] Speaker B: Oh, certainly, certainly, you know, well, a model, the same thing with a model or a thought experiment or, you know, a thought experiment, in a way, is a contradiction. It's a weird oxymoron. It's a contradiction in terms. Like you, if you are just sitting around in your head thinking you are doing the opposite of an experiment, right?
A real experiment is you do something in reality and see the result. And, of course, the key difference there is when you do something in reality and see the result, you know that it's reality creating the result and not you just imagining it, right? So it's very easy when people do quote unquote, thought experiments, that the basic.
The basic problem or the basic pitfall of the thought that the danger of a thought experiment is that everything's coming out of your own mind, out of your own thoughts. So it's.
So it's very. So what you're doing is you're the relying on all the existing knowledge you already have about the things that you're thinking about, and you're projecting from that existing knowledge, but you're not. You don't have new knowledge and new facts that you're gaining about it. So it really allows you to sort of project what you already think and then say, oh, I did a thought experiment, but thought. And yet, nevertheless, thought experiments can be useful. I managed camera both. One, suppose, you know, suppose you're looking at a crowd. You look at only people with red coats. That's the thought experiment. Right? So I came up with that. I didn't actually go look at a crowd and do that. I imagined myself looking at a crowd. So. But now when you do that, though, you are, you know, you're creating this sort of projection, this imagination of what would happen if. And you have to be confident, or at least you have to be willing to test whether you're really right about that. Now, in terms of, you know, what? If I were looking at a crowd and I looked for only people in red coats, that's something that's so close to everyday experience that I think, you know, it's pretty. You have a high degree of confidence. I would even put it to a certainty that I can project what it would be like to do that. I can imagine doing that because I've done similar things. So here's a great big pluck, a real world example out of this, which is one that always struck me. There was a guy, actually, I think it was Radek Sikorsky, who's now, who's a figure of the polish government, a high ranking politician in Poland. But he talked about, I remember once him recounting when he was a young man, this is the end, the last years of soviet rule or communist rule in Poland. And John Paul II, Pope John Paul II came to Poland very famously in 1980. He was the Polish pope. He came back to his homeland, and the communists pooh poohed him because they were officially atheists. They were like, oh, only a few old ladies will turn out. Nobody really cares about the pope. It doesn't really matter. And of course, what happened is massive, enormous crowds turned out for the pope. Millions and millions of people, like 2 million people turned out to see him. This, this incredible sea of humanity, you know, coming to see the pope. And Sikorsky talks about climbing up in a tree and looking at seeing this vast. We get this higher perspective, seeing this vast crowd. And then off of the edges and nervous, nervous little clusters here. And there were the security services, you know, the secret police, the guys who were supposed to be doing the crowd control. And he suddenly had this realization. He said, there are so few of them and so many of us. And it's this perspective change he had, that, a realizing of how few people there were actually enforcing this communist regime, as opposed to the number of people who really didn't believe in the communist regime and didn't support it and who would abandon it in the moment if they thought they could get, if they weren't afraid. And it was just like this evaporation of fear that comes with realizing how many of us there are and how few of them. So there's an example of somebody, a real life example of somebody looking out at a crowd, doing a selective mental focus. How many of these people are ordinary people who came to see the pope? How many of these people are security services who are here to enforce the will of the regime and then getting a real profound result from that change in mental perspective. So there's that. There's a real life example of you're not looking for people with red coats, you're looking for people with, you know, with uniforms and, and other, other things that mark them as members of the regime, and you're getting this, this real profound information as a result of that. So that's, I think, a real plucking from the real world. Somebody's real world record, elections, an example.
[00:49:11] Speaker A: Very good. Uh, there's still time, if you have a question. I've still got more three world epistemology. I mean, how much of that is Plato's duality with the third layer?
[00:49:23] Speaker B: Well, I think it absolutely.
It's an echo of Plato. So the difference now, the difference. And what makes popper better? Popper is better than Plato. I think scientists like him better than Plato for this reason, which is that the greek philosopher Plato had the idea that there's, you know, that there's the real world, there's your perceptions, these sort of fleeting, imperfect perceptions. We have the real world, and then there's our conceptions, which refer to another world, a world of pure forms and this world of abstractions that's separate from the real world. And that is very much, you know, Popper's idea of this sort of, I call it third world epistemology is because I like to contrast it to first world. You know, ours is first world epistemology. It's the better epistemology. It's, it's wealthier and more luxurious cetera.
But the third world epistemology is definitely an echo of that platonic approach, that there's a realm of abstractions that's different from. It's a whole different world disconnected from the realm of observation, the realm of real things in this world.
And the difference now, the difference in what makes Popper slightly better is that he doesn't actually think that the third world has a sort of independent.
He doesn't think it comes first. So in Plato's idea that the world of abstractions is so much better, it's so much neater, it's so much more perfect.
I talked about the occupational hazard of the intellectual is we're fascinated with ideas. And so the problem is ideas can become so interesting to you. They're more interesting than reality. And Plato's the perfect example of the guy who took this all the way, right? The. The world of abstractions is so much neater, so much purer that. That. That schematic in my mind, that that geometric schematic of a sphere is so much more perfect and pure than any actual round thing I've ever seen in the real world. And so therefore, it must be superior and better. It's the real world. That's the world that really exists, and everything else is. The world we live in is just imperfect reflection of it. Right?
[00:51:36] Speaker A: That.
[00:51:36] Speaker B: And that is the platonic view of the world. The ancient greek philosopher Plato. That's his view of the world in a nutshell. All right, so. And the problem with that is, you know, your problems with that are myriad, right? Because you then ignore the real world. And what's better about. About Popper is he kind of concedes a sort of a more Aristotle approach, whereas, like, no, the real. You know, Aristotle was Plato's student, but he reversed the whole thing. He said, no, the world of objects is what exists. And abstractions are all just taken from that. They're based on that, and they refer back to it. And so the abstractions are not more real than the concretes. The concretes are the reality. And the abstractions have to be based on that in some way or reflect it in some way. Now, he wasn't, you know, he has some elements of representationalism in his view, but he would. That was much more his approach. And popper sort of concedes that. Right. But he then has this idea of, well, mentally, what's going on is you're making these. You're creating this mental world of models that. That has to be compared back to the facts of the world. And I said that, you know, it's less damaging because he has. He has the idea. No, you have to compare it back to the world. The real world. The real world is your ultimate standard, sort of experimentally, factually. What happens.
What happens when you create an experiment? You get an actual result. That's the standard.
But in his idea of how you create the abstractions, it's the idea. You create them by going farther and farther away from the facts. And I think that creates a lot of pitfalls in terms of how people think. So it sort of produces this leftover echo of Plato within an aristotelian world focused viewpoint.
[00:53:26] Speaker A: You've found a valid sense to use the world out there when it's to one of those intellectuals that's stuck in the world of ideas.
[00:53:36] Speaker B: Yeah.
[00:53:37] Speaker A: How about the idea that JP, Jordan Peterson and others talk about the heuristic model of learning that we learn through stories?
[00:53:46] Speaker B: Yes.
[00:53:47] Speaker A: Is that. I mean, is that a useful model?
[00:53:51] Speaker B: I'm not an expert on that. I think he's right. That we learned through stories. He's wrong, I think from what I know. Again, I'm not Jordan Peterson expert.
I've become less inclined to become one because the things he said recently that I don't know, especially things about Ukraine, that indicate he's not thinking very clearly.
But what I would say is there's an old idea that people think through stories. And actually, I'm going to recommend my favorite. You know, I gotta do this. This, Scott, I'm gonna recommend one of my favorite Star Trek episodes.
This is Dharmak from the fifth season of Star Trek the Next Generation where they encounter alien species. The whole point is, it's a high, total high concept thing where the whole point is, you know, I mentioned pitching this to the pseudo executives.
[00:54:34] Speaker C: Right.
[00:54:34] Speaker A: Okay.
[00:54:34] Speaker B: So we're in the show where they're trying. Where the whole idea is that they're trying to communicate with a guy and they can't understand the single word he's saying. And half the episode is going to be Picard and this guy talking together where you can't understand the thing. Single thing the alien is saying. Right.
How do you sell that? They could only sell that in the fifth season after the thing was just a runaway hit. They were just saying, do whatever you like. All right, so. But the idea is that they come across this alien race that where they. Where, you know, they have this universal translator supposed to automatically translate everything that people say. And the universal translator doesn't work. It can't figure out how to translate their language. And it turns out that they all speak in metaphor. They all speak in stories and images and stories. So they sing like, dharma Jalad at Tanagra. And, you know, it refers to a story about a character named Dharmak and a character named Jalad in this place called Tanagra. And what happened to the characters there? And that's their way of communicating something. Or they say, Rai and Jiri at the crossroads, and there's two characters, and there was something that happened at a crossroads where they met. And you're supposed to understand what's happening because you understand the story. And of course, if you don't know the stories, if you don't have the folklore behind it, it's going to be incomprehensible to you, which is why the translator won't work. Well, this is a real way that people think. And it. And I wrote a whole article once about how a lot of our politics works this way. So a lot of our politics is the bridge at Selma, you know, so. And, you know, this is where we. Or Washington at Valley Forge. And, you know, we're referring to these. These stories and these narratives. But the problem you see in our politics is, of course, you know, people, the problem with thinking in terms of stories and learning through stories is it can be valuable. Stories are helpful. I just told you a story about this guy from this polish politician, I think Roddick Sikorsky is his name, who. Who climbed a tree and saw, you know, the crowd. I told you a story, and you learned something from it. Right? The problem is that when the narrative becomes. Again, it's the same problem with models. It's when the narrative becomes the central focus and not the facts that it's steering you to. So, you know, the narrative or a model or a narrative or a story can be useful as a way of steering you to certain facts, but then you have to then go all the way and go to the facts. And, you know, there's a longstanding complaint about what's called narrative journalism, right, where some. Where originally, narrative journalism referred to the idea of, you don't just report a dry series of facts. You tell it as if it were a story. But then narrative journalism can also become. And I've seen it practice on both the left and the right. It can become. You come up with the story first. You like the story. The story works. It feels satisfying to you. It suits your political purposes or your biases or, you know, what you want to stampede people into. And then you fit the facts into the story. So you come up with the story first and the facts later.
And so, again, it's this thing of, you know, if you have this idea of models or narratives as the central thing of cognition rather than just as tools to get you to a more exact and literal description of facts and grasp of facts, you're gonna go off. You're gonna go off the rails, and you're gonna go out. You're gonna have, you know, what we often get in the press of people who have a preferred narrative that they wanted to fit. And then everything my. I guess, my. The one that I know so I don't want to pick one side of the debate, because it's done liberally on both sides.
But the one that drops to my mind is there's a Twitter feed called died suddenly, and it's a bunch of anti vaccine. And, you know, COVID. COVID people, people who are anti vaccine. And so the whole purpose of this Twitter feed is anytime somebody who seems young and healthy dies suddenly, they report it. Like, you know, and of course they report that, oh, he was vaccinated. And the idea is supposed to be, therefore, can't you see it? That's the vaccine that killed him. And the ghoulish thing about it is, if you actually look at, you know, if you actually follow the stories and look up what's, you know, they report these things. If somebody died suddenly, they do it without looking into any of the medical history, having any knowledge of what actually killed the person. And, and if you can get information on some of these, they've had these cases where people followed this up. What's the real information? It turns out, well, the guy was a major drug addict, right? He basically had a spoon up his nose all the time. And he didn't die suddenly. He died of a drug overdose because he was a drug addict or, you know, he died suddenly. But it turns out they did the autopsy and he had a congenital heart defect. And so the guy was 32 years old and seemingly very healthy, but he'd been living his whole life with something that was going to kill him at any moment. He just didn't know it. So again, this is a case of somebody taking a narrative that they, like the vaccines, are killing people and then scanning the world for facts to shove into that narrative. So that's the problem with, you know. So learning through stories is very valuable. We all do it. I've done it in this last hour. But again, you have to always keep in mind, it's just a way of getting you to a perspective on the facts that is based on literal, verifiable facts and not taking the story first or the model first and fitting the facts and choosing cherry picking the facts to fit it.
[01:00:02] Speaker A: Great. Well, that takes us to the bottom of the hour. It was a great discussion, Rob. We look forward to the completed project, and thanks to everyone who participated. If you enjoyed this or any of our other materials, please consider making a tax deductible donation at Atlas Society. Thanks for joining. We'll see you next week.
